Title :
Multi-objective performance optimization of H.264 AVC encoder
Author :
Al-Abri, F. ; Li, X. ; Edirisinghe, E.A. ; Grecos, C.
Author_Institution :
Dept. of Comput. Sci., Loughborough Univ., Loughborough, UK
Abstract :
We propose a multi-objective optimization framework based on genetic algorithms to enhance the performance of a video codec. The framework is designed to jointly minimize the complexity, memory usage in the encoder, bit rate and maximize the quality of the compressed video stream. In particular, the optimization framework is designed to determine the optimum coding parameters for the H.264 AVC video codec in a memory and bandwidth constrained environments. This was demonstrated through extensive experiments and mathematical formulation that resulted in the optimum solution for the optimization problem as the final outcome.
Keywords :
data compression; genetic algorithms; video coding; H.264 AVC encoder; bandwidth-constrained environment; bit rate; complexity minimization; genetic algorithms; memory usage; multiobjective performance optimization; video codec; video stream compression; Automatic voltage control; Bit rate; Computational complexity; Computer science; Constraint optimization; Genetic algorithms; Streaming media; Video codecs; Video coding; Video compression; H.264 AVC; Multi-objective optimization; Video coding;
Conference_Titel :
Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
Conference_Location :
Cardiff
Print_ISBN :
978-1-4244-2709-3
Electronic_ISBN :
978-1-4244-2711-6
DOI :
10.1109/SSP.2009.5278457